Pro+: Automated protrusion and critical shear stress estimates from 3D point clouds of gravel beds

Yager, Elowyn M.; Shim, Jaeho; Hodge, Rebecca; Monsalve, Angel; Tonina, Daniele; Johnson, Joel P. L.; Telfer, Luke

Abstract

The dimensionless critical shear stress (τ*c) needed for the onset of sediment motion is important for a range of studies from river restoration projects to landscape evolution calculations. Many studies simply assume a τ*c value within the large range of scatter observed in gravel-bedded rivers because direct field estimates are difficult to obtain. Informed choices of reach-scale τ*c values could instead be obtained from force balance calculations that include particle-scale bed structure and flow conditions. Particle-scale bed structure is also difficult to measure, precluding wide adoption of such force-balance τ*c values. Recent studies have demonstrated that bed grain size distributions (GSD) can be determined from detailed point clouds (e.g. using G3Point open-source software). We build on these point cloud methods to introduce Pro+, software that estimates particle-scale protrusion distributions and τ*c for each grain size and for the entire bed using a force-balance model. We validated G3Point and Pro+ using two laboratory flume experiments with different grain size distributions and bed topographies. Commonly used definitions of protrusion may not produce representative τ*c distributions, and Pro+ includes new protrusion definitions to better include flow and bed structure influences on particle mobility. The combined G3Point/Pro+ provided accurate grain size, protrusion and τ*c distributions with simple GSD calibration. The largest source of error in protrusion and τ*c distributions were from incorrect grain boundaries and grain locations in G3Point, and calibration of grain software beyond comparing GSD is likely needed. Pro+ can be coupled with grain identifying software and relatively easily obtainable data to provide informed estimates of τ*c. These could replace arbitrary choices of τ*c and potentially improve channel stability and sediment transport estimates.

Citation

Yager, E. M., Shim, J., Hodge, R., Monsalve, A., Tonina, D., Johnson, J. P. L., & Telfer, L. (2024). Pro+: Automated protrusion and critical shear stress estimates from 3D point clouds of gravel beds. Earth Surface Processes and Landforms, 49(7), 2155-2170. https://doi.org/10.1002/esp.5822

• Journal Article Type: Article
• Acceptance Date: Mar 3, 2024
• Online Publication Date: Apr 4, 2024
• Publication Date: Jun 15, 2024
• Deposit Date: Apr 9, 2024
• Publicly Available Date: Apr 11, 2024
• Journal: Earth Surface Processes and Landforms
• Print ISSN: 0197-9337
• Electronic ISSN: 1096-9837
• Publisher: British Society for Geomorphology
• Peer Reviewed: Peer Reviewed
• Volume: 49
• Issue: 7
• Pages: 2155-2170
• DOI: https://doi.org/10.1002/esp.5822
• Keywords: Earth and Planetary Sciences (miscellaneous); Earth-Surface Processes; Geography, Planning and Development
• Public URL: https://durham-repository.worktribe.com/output/2379724